CN-121979141-A - Intelligent control system and control method for processing roasted aconite

CN121979141ACN 121979141 ACN121979141 ACN 121979141ACN-121979141-A

Abstract

The invention relates to the technical field of processing of roasted aconite, and discloses an intelligent control system and a control method for processing roasted aconite, wherein the intelligent control system comprises a processing monitoring module, an intelligent early warning module and a finished product detection module, the processing monitoring module is used for monitoring key parameters of the whole processing flow, automatically adjusting the running state of equipment and sending monitoring results and real-time monitoring values of the key parameters to the intelligent early warning module. The system establishes multidimensional and time-sequential process sensing capability through synchronous real-time acquisition and analysis of key parameters such as temperature, oxygen content, humidity, bran consumption rate and the like at each sampling moment and tail gas components by the processing monitoring module, and can automatically adjust equipment operation when the parameters are abnormal, thereby greatly improving process stability and product batch consistency, reducing dependence on experience operation, and adopting a nondestructive sensing judgment method of comparing a knocking voiceprint with a historical database, rapidly identifying and automatically eliminating unqualified products and remarkably improving the detection rate.

Inventors

XUE YANHUA
YI BIN
YAN JIAJUN
HAN QILIN
CUI JIAQUAN

Assignees

建昌帮药业有限公司
建昌帮中医药研究(江西)有限公司
建昌帮(江西)医药销售有限公司

Dates

Publication Date: 20260505
Application Date: 20260119

Claims (10)

1. An intelligent control system for processing simmer aconite is characterized by comprising a processing monitoring module, an intelligent early warning module and a finished product detection module; The processing monitoring module is used for monitoring key parameters of the whole processing flow, automatically adjusting the running state of equipment when the key parameters are abnormal, simultaneously monitoring tail gas of the processing flow, and sending a monitoring result and a real-time monitoring value of the key parameters to the intelligent early warning module; The intelligent early warning module is used for detecting and early warning the tail gas of the processing flow, early warning is carried out when the processed tail gas exceeds a preset tail gas early warning value, the intelligent early warning module monitors key parameters of the processing flow in real time and calculates deviation coefficients of any key parameters in real time, and early warning is carried out when the deviation coefficient of any key parameter exceeds a preset deviation threshold value; the finished product detection module is used for detecting finished products after processing, comparing the processed finished products with the knocking voiceprints in the historical database, calculating a finished product deviation coefficient, judging that the finished products are unqualified when the finished product deviation coefficient exceeds a set threshold value, and rejecting the finished products.
2. The intelligent control system for processing roasted slices of dried aconite as claimed in claim 1, wherein the processing monitoring module comprises a key parameter detection unit and an exhaust gas parameter detection unit; The key parameter detection unit is used for collecting key parameters in the processing process, specifically comprises temperature, oxygen content, humidity and chaff consumption rate at each sampling moment, compares the temperature, oxygen content, humidity and chaff consumption rate with historical data, calculates a first deviation coefficient, and specifically comprises the following expression: Wherein, the A first coefficient of deviation is indicated and, Representation of Time of day The key parameter specific values acquired by the sensors, Represents the maximum value of the key parameter, Representing the key parameter minimum.
3. The intelligent control system for processing roasted slices as claimed in claim 2, wherein the key parameter detection unit is arranged in the first deviation coefficient And calculating a second deviation coefficient, wherein the specific expression is as follows: Wherein, the A second coefficient of deviation is indicated and, Representing the summation of all the key parameters, Representation of Time of day The key parameter specific values acquired by the sensors, Representing the total number of categories of key parameters, The first to indicate the historical time The key parameter mean value acquired by each sensor, Representing the absolute value.
4. The intelligent control system for simmer with chips processing as defined in claim 2, wherein the tail gas parameter detecting unit reads the concentration of harmful gas before tail gas treatment and the concentration of harmful gas after tail gas treatment, and calculates the current bran consumption rate in the key parameters based on the concentration of harmful gas before tail gas treatment, and the specific expression is as follows: Wherein, the Indicating the rate of consumption of the chaff, Represents the mass consumption rate of the bran coat, Represents the volume of the gas phase space, Represents the molar mass of the carbon and, Representing the mass fraction of carbon in the chaff.
5. The intelligent control system for processing roasted aconite slice as claimed in claim 3, wherein the intelligent early warning module reads When the processing method is used, a first early warning instruction is sent out to remind a worker of parameter unbalance in the processing process, the worker is required to overhaul equipment after the processing is finished, and current recorded data are stored independently; the intelligent early warning module reads When waiting for the key parameter detection unit to calculate the second deviation coefficient, if Exceeding a preset deviation threshold And sending out a second early warning instruction, and calculating a specific deviation rate, wherein the specific expression is as follows: Wherein, the Representing the deviation rate.
6. The intelligent control system for simmer with a piece processing as claimed in claim 4, wherein the intelligent early warning module compares the concentration of the harmful gas after the exhaust gas treatment is read with a corresponding harmful gas emission threshold value, if the concentration of the harmful gas exceeds the corresponding harmful gas emission threshold value, the intelligent early warning module sends an exhaust gas early warning instruction, dispatches staff to overhaul, and simultaneously automatically accesses a standby exhaust gas treatment pipeline.
7. The intelligent control system for processing roasted slices as claimed in claim 5, wherein the finished product detection module is invoked after reaching a preset processing time, detects the processed finished product, calculates a finished product deviation coefficient by comparing the processed finished product with the knocked voiceprints in the history database, judges the finished product to be unqualified when the finished product deviation coefficient exceeds a set threshold value, rejects the finished product, and invokes the cleaning equipment to clean the processed product after the finished product detection module is output to be qualified.
8. The intelligent control system for processing roasted slices as claimed in claim 7, wherein the product deviation coefficient The calculated expression of (2) is as follows: Wherein, the And The weight coefficient is represented by a number of weight coefficients, , Representing the peak amplitude deviation of the audio signal, Representing the deviation amplification factor, if Then If (if) Does not exceed a preset deviation threshold Then If (if) Exceeding a preset deviation threshold Then , Representing the root mean square deviation of the audio signal, Representing the deviation rate.
9. The intelligent control system for processing roasted slices as claimed in claim 8, wherein the peak amplitude deviation The specific expression of (2) is as follows: Wherein, the Representing the average value of the maximum value of the historical amplitude, Representing the average of the minimum values of the historical amplitude, Representing the maximum value of the amplitude of the current audio signal, Representing the amplitude minimum of the current audio signal, Representing the absolute value.
10. An intelligent control method for processing roasted aconite, based on the intelligent control system for processing roasted aconite according to any one of claims 1-9, characterized by comprising the following steps: S1, feeding, processing aconite, monitoring key parameters of the whole processing flow through a processing monitoring module, automatically adjusting the running state of equipment when the key parameters are abnormal, monitoring tail gas of the processing flow, and sending a monitoring result and a real-time monitoring value of the key parameters to an intelligent early warning module; S2, in the smoldering process, the intelligent early-warning module detects and early-warns the tail gas of the processing flow, when the processed tail gas exceeds a preset tail gas early-warning value, simultaneously monitors key parameters of the processing flow in real time and calculates deviation coefficients of any key parameters in real time, and when the deviation coefficient of any key parameter exceeds a preset deviation threshold value, early-warns; S3, discharging after the stewing time reaches a preset value, detecting finished products after processing, comparing the finished products after processing with the knocking voiceprints in the historical database, calculating a finished product deviation coefficient, judging that the finished products are unqualified when the finished product deviation coefficient exceeds a set threshold value, and rejecting the finished products; And S4, after the output of the finished product detection module is qualified, the cleaning equipment is called to clean the processed product.

Description

Intelligent control system and control method for processing roasted aconite Technical Field The invention relates to the technical field of processing of roasted aconite, in particular to an intelligent control system and a control method for processing roasted aconite. Background The core of the roasted aconite is stable smoldering combustion of bran, the bran is gradually consumed as fuel along with the combustion time, and the processing technology of the roasted aconite is a key link for ensuring the efficacy, safety and stability. The traditional processing is mostly dependent on craftsman experience, and the heating temperature, time, fire and stirring time are determined by subjective judgment of observing color, smell, hand feeling, tapping sound and the like. With the development of large-scale and industrial production, the requirements of quality consistency, traceability and environmental protection are difficult to meet by manual experience alone, and the processing technology is promoted to develop towards automation and intellectualization; However, the existing quality detection is dependent on manual spot check or laboratory test, the detection period is long, unqualified products are difficult to remove in real time on line, the utilization of perception features such as acoustics is less, an automatic judging mechanism for comparison with a historical database is not formed, and the existing technology is insufficient for realizing the fine and intelligent control and on-line quality judgment of the whole processing process of the roasted aconite. Disclosure of Invention Aiming at the defects of the prior art, the invention provides an intelligent control system and a control method for processing roasted aconite, which have the advantages of fine control of the whole processing process of roasted aconite, real-time rejection of defective products and the like, and solve the technical problems. In order to achieve the aim, the invention provides the following technical scheme that the roasted aconite processing intelligent control system comprises a processing monitoring module, an intelligent early warning module and a finished product detection module; The processing monitoring module is used for monitoring key parameters of the whole processing flow, automatically adjusting the running state of equipment when the key parameters are abnormal, simultaneously monitoring tail gas of the processing flow, and sending a monitoring result and a real-time monitoring value of the key parameters to the intelligent early warning module; The intelligent early warning module is used for detecting and early warning the tail gas of the processing flow, early warning is carried out when the processed tail gas exceeds a preset tail gas early warning value, the intelligent early warning module monitors key parameters of the processing flow in real time and calculates deviation coefficients of any key parameters in real time, and early warning is carried out when the deviation coefficient of any key parameter exceeds a preset deviation threshold value; the finished product detection module is used for detecting finished products after processing, comparing the processed finished products with the knocking voiceprints in the historical database, calculating a finished product deviation coefficient, judging that the finished products are unqualified when the finished product deviation coefficient exceeds a set threshold value, and rejecting the finished products. As a preferable technical scheme of the invention, the processing monitoring module comprises a key parameter detection unit and a tail gas parameter detection unit; The key parameter detection unit is used for collecting key parameters in the processing process, specifically comprises temperature, oxygen content, humidity and chaff consumption rate at each sampling moment, compares the temperature, oxygen content, humidity and chaff consumption rate with historical data, calculates a first deviation coefficient, and specifically comprises the following expression: Wherein, the A first coefficient of deviation is indicated and,Representation ofTime of dayThe key parameter specific values acquired by the sensors,Represents the maximum value of the key parameter,Representing the key parameter minimum. As a preferable solution of the present invention, the key parameter detecting unit is configured to detect the key parameter in the first deviation coefficientAnd calculating a second deviation coefficient, wherein the specific expression is as follows: Wherein, the A second coefficient of deviation is indicated and,Representing the summation of all the key parameters,Representation ofTime of dayThe key parameter specific values acquired by the sensors,Representing the total number of categories of key parameters,The first to indicate the historical timeThe key parameter mean value acquired by each sensor,Representing the absolute value. As a prefer